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  • 1
    Online Resource
    Online Resource
    NIMG-55. AUGMENTED INTELLIGENCE IS SUPERIOR TO ARTIFICIAL INTELLIGENCE! HUMAN-COMPUTER SYNERGY FOR GENERATING HIGH QUALITY GLIOBLASTOMA SUB-REGION SEGMENTATIONS
    Oxford University Press (OUP) ; 2021
    In:  Neuro-Oncology Vol. 23, No. Supplement_6 ( 2021-11-12), p. vi141-vi142
    Details
    In: Neuro-Oncology, Oxford University Press (OUP), Vol. 23, No. Supplement_6 ( 2021-11-12), p. vi141-vi142
    Abstract: Artificial intelligence (AI) is poised to improve diagnostic methods in neuro-oncologic imaging and contribute to patient management by analyzing pre-operative MRI scans. AI results are better interpreted by compartmentalizing glioblastoma into distinct sub-regions, i.e., necrotic core, enhancing tumor, peritumoral T2/FLAIR signal abnormality (ED). Manual delineation of these sub-regions by expert neuroradiologists is impractical, requiring hours for intricate cases. Computer-aided segmentation (CAS) can mitigate this issue but is limited in the quality of the produced segmentations. We hypothesize that CAS followed by expert refinements is more practical/time-efficient. METHODS CAS was used on a total of 359 glioblastoma patients with four MRI sequences (T1, T1Gd, T2, T2-FLAIR) from each patient. All segmentations were sent to expert neuroradiologist annotators for manual refinements. Once refined, our team including two senior attending neuroradiologists with ≥13 years of experience each, reviewed and either approved or returned the segmentations to individual annotators for further refinements. Total time required to refine and review the finalized segmentations was measured. RESULTS Following one round of refinements by expert annotators, 244/359 (68%) segmentations were approved by our team while 115/359 (32%) segmentations contained a variety of errors that required a second round of refinements. The most common observed errors were 1) missed ED in the anterior/inferior temporal lobes and corpus callosum (37/115 cases, 32%) and 2) erroneous segmentation of normal choroid plexus and blood vessels (14/115 cases, 12%). The expert annotators required 120 hours to refine all 359 segmentations, and our team required 26 additional hours to review them, resulting in 24 minutes/segmentation following CAS. CONCLUSION Our findings support the value of a well-communicated annotation protocol to coordinate CAS and expert annotators. With CAS, our team and expert annotators rapidly finalized segmentations for 359 glioblastoma patients, demonstrating the value of a synergistic approach to creating high quality tumor sub-region segmentations.
    Type of Medium: Online Resource
    ISSN: 1522-8517 , 1523-5866
    URL: Article
    DOI: 10.1093/neuonc/noab196.553
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2021
    detail.hit.zdb_id: 2094060-9
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  • 2
    Online Resource
    Online Resource
    NIMG-45. DISTINGUISHING PROGRESSION FROM PSEUDOPROGRESSION IN GLIOBLASTOMA: COMBINED USE OF 18F-FLUCICLOVINE PET AND MULTI-PARAMETRIC MRI
    Oxford University Press (OUP) ; 2022
    In:  Neuro-Oncology Vol. 24, No. Supplement_7 ( 2022-11-14), p. vii173-vii173
    Details
    In: Neuro-Oncology, Oxford University Press (OUP), Vol. 24, No. Supplement_7 ( 2022-11-14), p. vii173-vii173
    Abstract: Differentiation of tumor progression (TP) from pseudoprogression (PsP) is a major unmet need in post-treatment glioblastoma (GBM). 18F-Fluciclovine is a synthetic amino acid PET radiotracer with higher uptake in tumor tissue vs. areas of treatment-related change. We investigated the value of 18F-Fluciclovine PET for differentiating PsP from TP independent from and in combination with multi-parametric MRI. METHODS We prospectively enrolled 30 patients with GBM with a new or enlarging contrast-enhancing lesion on MRI after chemoradiotherapy who were planned for surgical resection of the lesion. Patients underwent pre-operative 18F-Fluciclovine PET and multi-parametric MRI. Following surgery, the relative percentages of viable tumor and therapy-related changes observed in histopathology were quantified. Patients were categorized as TP if viable tumor represented ≥ 50% of the specimen, mixed TP if & lt; 50% and & gt; 10%, and PsP if ≤ 10%. RESULTS 18 patients had TP, 4 had mixed TP, and 8 PsP. Patients with TP/mixed TP had a significantly higher 40-50 minutes SUVmax (6.64 + 1.88 vs 4.11± 1.52, p=0.009) and an SUVmax cut-off of 4.66 provided 90% sensitivity and 83% specificity for differentiation of TP/mixed TP from PsP (AUC=0.856). A maximum cerebral blood volume (CBVmax) cut-off of 3.67 provided 90% sensitivity and 71% specificity for differentiation of TP/mixed TP from PsP (AUC=0.779). Combining a 40-50 minutes SUVmax cut-off of 4.662 and a relative CBVmax cut-off of 3.67 provided 100% sensitivity and 80% specificity for differentiating TP/mixed TP from PsP (AUC=0.95). The time activity curve patterns and time to peaks were not different between the groups. Normalization of PET parameters to normal brain parenchyma were not helpful to differentiate the groups due to variability in radiotracer uptake in normal brain between subjects. CONCLUSION 18F-Fluciclovine PET uptake can accurately differentiate PsP from TP in GBM patients, with even more accurate differentiation achieved when combined with MRI.
    Type of Medium: Online Resource
    ISSN: 1522-8517 , 1523-5866
    URL: Article
    DOI: 10.1093/neuonc/noac209.663
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2022
    detail.hit.zdb_id: 2094060-9
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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